Computational model of the cerebellar cortex

2023-05-17T17:18:16+01:00

This week on Journal Club session Eleonora Bernasconi will present her work about "Computational model of the cerebellar cortex". Please find below to see the abstract of one of the related papers.

Climbing fibers (CFs) provide instructive signals driving cerebellar learning, but mechanisms causing the variable CF responses in Purkinje cells (PCs) are not fully understood. Using a new experimentally validated PC model, we unveil the ionic mechanisms underlying CF-evoked distinct spike waveforms on different parts of the PC. We demonstrate that voltage can gate both the amplitude and the spatial range of CF-evoked Ca2+ influx by the availability of K+ currents. This makes the energy consumed during a complex spike (CS) also voltage dependent. PC dendrites exhibit inhomogeneous excitability with individual branches as computational units for CF input. The variability of somatic CSs can be explained by voltage state, CF activation phase, and instantaneous CF firing rate. Concurrent clustered synaptic inputs affect CSs by modulating dendritic responses in a spatially precise way. The voltage- and branch-specific CF responses can increase dendritic computational capacity and enable PCs to actively integrate CF signals.

Papers:

Y. Zang, S. Dieudonn'e, E. De, Schutter, "Voltage- and Branch-Specific Climbing Fiber Responses in Purkinje Cells", 2018, Cell Reports, 24, 1536--1549
S. Sudhakar, S. Hong, I. Raikov, R. Publio, C. Lang, T. Close, D. Guo, M. Negrello, E. De, Schutter, "Spatiotemporal Network Coding of Physiological Mossy Fiber Inputs by the Cerebellar Granular Layer", 2017, PLoS computational biology, 13, e1005754

Date: 2023/05/19
Time: 14:00
Location: online

Bursting Neurons Signal Input Slope

2021-04-21T11:37:00+01:00

This week on Journal Club session Volker Steuber will talk about a paper "Bursting Neurons Signal Input Slope".

Brief bursts of high-frequency action potentials represent a common firing mode of pyramidal neurons, and there are indications that they represent a special neural code. It is therefore of interest to determine whether there are particular spatial and temporal features of neuronal inputs that trigger bursts. Recent work on pyramidal cells indicates that bursts can be initiated by a specific spatial arrangement of inputs in which there is coincident proximal and distal dendritic excitation (Larkum et al., 1999). Here we have used a computational model of an important class of bursting neurons to investigate whether there are special temporal features of inputs that trigger bursts. We find that when a model pyramidal neuron receives sinusoidally or randomly varying inputs, bursts occur preferentially on the positive slope of the input signal. We further find that the number of spikes per burst can signal the magnitude of the slope in a graded manner. We show how these computations can be understood in terms of the biophysical mechanism of burst generation. There are several examples in the literature suggesting that bursts indeed occur preferentially on positive slopes (Guido et al., 1992; Gabbiani et al., 1996). Our results suggest that this selectivity could be a simple consequence of the biophysics of burst generation. Our observations also raise the possibility that neurons use a burst duration code useful for rapid information transmission. This possibility could be further examined experimentally by looking for correlations between burst duration and stimulus variables.

Papers:

A. Kepecs, X. Wang, J. Lisman, "Bursting Neurons Signal Input Slope", 2002, The Journal of Neuroscience, 22, 9053--9062

Date: 2021/04/23
Time: 14:00
Location: online

UH Biocomputation Group - biophysical model

Computational model of the cerebellar cortex

Bursting Neurons Signal Input Slope